retention-optimization-expert
Reduce churn and improve retention through cohort analysis, at-risk user identification, win-back campaigns, and customer success strategies. Generate comprehensive HTML reports with retention curves, health scores, churn analysis, and 90-day implementation roadmaps.
Profile →npx skills add majiayu000/claude-skill-registry --skill retention-optimization-expert-maigentic-stratarts-1b907ee1 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The skill focuses on reducing churn and boosting retention by performing cohort analysis, identifying at-risk users, designing win-back campaigns, and outlining customer success strategies. It also generates HTML reports that include retention curves, health scores, churn analysis, and a 90-day implementation roadmap.
How it works
The skill provides a structured workflow across multiple sections:
- Pre-Generation Verification: requires data points such as company name, date, 30/7-day retention, churn, at-risk percentage, health, curve type, and executive summaries for the HTML output.
- Data sections and prompts guide the agent to fill in cohort data (M0–M6), segment retention, at-risk indicators, health scores, win-back tiers, churn reasons, retention loops, CS model details, charts data, success metrics, and a four-phase roadmap.
- The workflow enumerates explicit questions and data blocks (e.g., header banners, cohort tables, segment cards, risk indicators, win-back tiers, churn reasons, loops, CS touchpoints, and charts) to assemble the final HTML report.
- Step-by-step prompts specify exact content to capture (e.g., D30 retention, M3 retention, at-risk criteria, actions per tier, and success metrics).
When to use it
Use when you need a retention-focused analytics and action-plan document. It is designed to produce a comprehensive HTML report with retention metrics, cohort behavior, at-risk identification, win-back campaigns, churn analysis, and a 90-day roadmap.
What it can touch
The skill declares the tool: claude-code. It structures data collection and report generation through sections that would be populated by the agent using the tool to fetch, compute, and render the HTML output.
Caveats
The plan requires accurate data for all header, executive, cohort, segment, risk, health, win-back, churn, loops, CS, charts, metrics, and roadmap sections. Missing sections are to be omitted per the data availability; no assumptions are stated beyond the explicit data blocks outlined in the workflow.
# retention-optimization-expert **Mission**: Reduce churn and improve retention through cohort analysis, at-risk user identification, win-back campaigns, product improvements, and customer success strategies. Turn one-time users into lifelong customers. --- ## STEP 0: Pre-Generation Verification Before generating the HTML output, verify all required data is collected: ### Header & Score Banner - [ ] `{{BUSINESS_NAME}}` - Company/product name - [ ] `{{DATE}}` - Report generation date - [ ] `{{D30_RETENTION}}` - 30-day retention rate (e.g., "38%") - [ ] `{{D7_RETENTION}}` - 7-day retention rate (e.g., "52%") - [ ] `{{CHURN_RATE}}` - Monthly churn rate (e.g., "6.2%") - [ ] `{{AT_RISK_PERCENT}}` - Percentage of at-risk users (e.g., "18%") - [ ] `{{HEALTH_GREEN}}` - Percentage of healthy users (e.g., "62%") - [ ] `{{CURVE_TYPE}}` - Short curve type (e.g., "Steep Drop + Plateau") ### Executive Summary - [ ] `{{EXECUTIVE_SUMMARY}}` - 2-3 paragraphs with retention overview, key interventions - [ ] `{{CURVE_TYPE_FULL}}` - Full curve description (e.g., "Steep Drop, Then Plateau (Good)") - [ ] `{{CURVE_DESCRIPTION}}` - Explanation of what the curve means for the business ### Cohort Analysis -
- STEP 0: Pre-Generation Verification
- Header & Score Banner
- Executive Summary
- Cohort Analysis
- Segment Retention
- At-Risk Identification
- Health Score
- Win-Back Campaign
- Churn Reasons
- Retention Loops
- Customer Success
- Charts
- Success Metrics
- Roadmap
What does the retention-optimization-expert skill do?
Reduce churn and improve retention through cohort analysis, at-risk user identification, win-back campaigns, and customer success strategies. Generate comprehensive HTML reports with retention curves, health scores, churn analysis, and 90-day implementation roadmaps.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill retention-optimization-expert-maigentic-stratarts-1b907ee1 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.